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Signal Processing of Power Quality Disturbances

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ISBN-10: 0471731684

ISBN-13: 9780471731689

Edition: 2006

Authors: Math H. J. Bollen, Irene Y. H. Gu, Irene Gu

List price: $208.95
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Bridging the gap between power quality and signal processing This innovative new text brings together two leading experts, one from signal processing and the other from power quality. Combining their fields of expertise, they set forth and investigate various types of power quality disturbances, how measurements of these disturbances are processed and interpreted, and, finally, the use and interpretation of power quality standards documents. As a practical aid to readers, the authors make a clear distinction between two types of power quality disturbances: Variations: disturbances that are continuously present Events: disturbances that occur occasionally A complete analysis and…    
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Book details

List price: $208.95
Copyright year: 2006
Publisher: John Wiley & Sons, Incorporated
Publication date: 8/4/2006
Binding: Hardcover
Pages: 888
Size: 6.36" wide x 9.29" long x 1.78" tall
Weight: 2.882
Language: English

Modern View of Power Systems
Power Quality
Interest in Power Quality
Definition of Power Quality
Events and Variations
Power Quality Monitoring
Signal Processing and Power Quality
Monitoring Process
Stationary and Nonstationary Signals
Machine Learning and Automatic Classification
Electromagnetic Compatibility Standards
Basic Principles
Stochastic Approach
Events and Variations
Three Phases
Overview of Power Quality Standards
Compatibility Between Equipment and Supply
Normal Operation
Normal Events
Abnormal Events
Distributed Generation
Impact of Distributed Generation on Current and Voltage Quality
Tripping of Generator Units
About This Book
Origin of Power Quality Variations
Voltage Frequency Variations
Power Balance
Power-Frequency Control
Consequences of Frequency Variations
Measurement Examples
Voltage Magnitude Variations
Effect of Voltage Variations on Equipment
Calculation of Voltage Magnitude
Voltage Control Methods
Voltage Unbalance
Symmetrical Components
Interpretation of Symmetrical Components
Power Definitions in Symmetrical Components: Basic Expressions
The dq-Transform
Origin of Unbalance
Consequences of Unbalance
Voltage Fluctuations and Light Flicker
Sources of Voltage Fluctuations
Description of Voltage Fluctuations
Light Flicker
Incandescent Lamps
Perception of Light Fluctuations
Flickermeter Standard
Flicker with Other Types of Lighting
Other Effects of Voltage Fluctuations
Waveform Distortion
Consequences of Waveform Distortion
Overview of Waveform Distortion
Harmonic Distortion
Sources of Waveform Distortion
Harmonic Propagation and Resonance
Summary and Conclusions
Voltage Frequency Variations
Voltage Magnitude Variations
Voltage Unbalance
Voltage Fluctuations and Flicker
Waveform Distortion
Processing of Stationary Signals
Overview of Methods
Parameters That Characterize Variations
Voltage Frequency Variations
Voltage Magnitude Variations
Waveform Distortion
Three-Phase Unbalance
Power Quality Indices
Total Harmonic Distortion
Crest Factor
Transformers: K-factor
Capacitor Banks
Motors and Generators
Telephone Interference Factor
Three-Phase Harmonic Measurements
Power and Power Factor
Frequency-Domain Analysis and Signal Transformation
Continuous and Discrete Fourier Series
Discrete Fourier Transform
Estimation of Harmonics and Interharmonics
Sinusoidal Models and High-Resolution Line Spectral Analysis
Multiple Signal Classification
Estimation of Signal Parameters via Rotational Invariance Techniques
Kalman Filters
Estimation of Broadband Spectrum
AR Models
ARMA Models
Summary and Conclusions
Frequency Variations
Voltage Magnitude Variations
Three-Phase Unbalance
Waveform Distortion
Methods for Spectral Analysis
General Issues
Further Reading
Processing of Nonstationary Signals
Overview of Some Nonstationary Power Quality Data Analysis Methods
Non-Model-Based Methods
Model-Based Methods
Discrete STFT for Analyzing Time-Evolving Signal Components
Interpretation of STFT as Bank of Subband Filters with Equal Bandwidth
Time Resolution and Frequency Resolution
Selecting Center Frequencies of Bandpass Filters
Leakage and Selection of Windows
Discrete Wavelet Transforms for Time-Scale Analysis of Disturbances
Structure of Multiscale Analysis and Synthesis Filter Banks
Conditions for Perfect Reconstruction
Orthogonal Two-Channel PR Filter Banks
Linear-Phase Two-Channel PR Filter Banks
Possibility for Two-Channel PR FIR Filter Banks with Both Linear-Phase and Orthogonality
Steps for Designing Two-Channel PR FIR Filter Banks
Consideration in Power Quality Data Analysis: Choosing Wavelets or STFTs?
Block-Based Modeling
Why Divide Data into Blocks?
Divide Data into Fixed-Size Blocks
Block-Based AR Modeling
Sliding-Window MUSIC and ESPRIT
Models Directly Applicable to Nonstationary Data
Kalman Filters
Discussion: Sliding-Window ESPRIT/MUSIC Versus Kalman Filter
Summary and Conclusion
Further Reading
Statistics of Variations
From Features to System Indices
Time Aggregation
Need for Aggregation
IEC 61000-4-30
Voltage and Current Steps
Very Short Variations
Phase Aggregation
Characteristics Versus Time
Arc-Furnace Voltages and Currents
Voltage Frequency
Voltage Magnitude
Very Short Variations
Harmonic Distortion
Site Indices
General Overview
Frequency Variations
Voltage Variations
Very Short Variations
Voltage Unbalance
Voltage Fluctuations and Flicker
Voltage Distortion
Combined Indices
System Indices
Frequency Variations
Voltage Variations
Voltage Fluctuations
Power Quality Objectives
Point of Common Coupling
Voltage Characteristics, Compatibility Levels, and Planning Levels
Voltage Characteristics EN 50160
Compatibility Levels: IEC 61000-2-2
Planning Levels: IEC 61000-3-6
Current Distortion by Customers: IEC 61000-3-6; IEEE Standard 519
Current Distortion by Equipment: IEC 61000-3-2
Other Power Quality Objectives
Summary and Conclusions
Origin of Power Quality Events
Causes of Interruptions
Restoration and Voltage Recovery
Multiple Interruptions
Voltage Dips
Causes of Voltage Dips
Voltage-Dip Examples
Voltage Dips in Three Phases
Phase-Angle Jumps Associated with Voltage Dips
Voltage Recovery After a Fault
What Are Transients?
Lightning Transients
Normal Switching Transients
Abnormal Switching Transients
Examples of Voltage and Current Transients
Summary and Conclusions
Voltage Dips
Other Events
Triggering and Segmentation
Overview of Existing Methods
Dips, Swells, and Interruptions
Other Proposed Methods
Basic Concepts of Triggering and Segmentation
Triggering Methods
Changes in rms or Waveforms
High-Pass Filters
Detecting Singular Points from Wavelet Transforms
Prominent Residuals from Models
Basic Idea for Segmentation of Disturbance Data
Using Residuals of Sinusoidal Models
Using Residuals of AR Models
Using Fundamental-Voltage Magnitude or rms Sequences
Using Time-Dependent Subband Components from Wavelets
Summary and Conclusions
Characterization of Power Quality Events
Voltage Magnitude Versus Time
Rms Voltage
Half-Cycle rms
Alternative Magnitude Definitions
Phase Angle Versus Time
Three-Phase Characteristics Versus Time
Symmetrical-Component Method
Implementation of Symmetrical-Component Method
Six-Phase Algorithm
Performance of Two Algorithms
Distortion During Event
Single-Event Indices: Interruptions
Single-Event Indices: Voltage Dips
Residual Voltage and Duration
Depth of a Voltage Dip
Definition of Reference Voltage
Sliding-Reference Voltage
Multiple-Threshold Setting
Uncertainty in Residual Voltage
Point on Wave
Phase-Angle Jump
Single-Index Methods
Single-Event Indices: Voltage Swells
Single-Event Indices Based on Three-Phase Characteristics
Additional Information from Dips and Interruptions
Extracting Transient Component
Transients: Single-Event Indices
Transients in Three Phases
Additional Information from Transients
Summary and Conclusions
Event Classification
Overview of Machine Data Learning Methods for Event Classification
Typical Steps Used in Classification System
Feature Extraction
Feature Optimization
Selection of Topologies or Architectures for Classifiers
Supervised/Unsupervised Learning
Learning Machines Using Linear Discriminants
Learning and Classification Using Probability Distributions
Hypothesis Tests and Decision Trees
Neyman-Pearson Approach
Bayesian Approach
Bayesian Belief Networks
Example of Sequential Classification of Fault-Induced Voltage Dips
Learning and Classification Using Artificial Neural Networks
Multilayer Perceptron Classifiers
Radial-Basis Function Networks
Applications to Classification of Power System Disturbances
Learning and Classification Using Support Vector Machines
Why Use a Support Vector Machine for Classification?
SVMs and Generalization Error
Case 1: SVMs for Linearly Separable Patterns
Case 2: Soft-Margin SVMs for Linearly Nonseparable Patterns
Selecting Kernels for SVMs and Mercer's Condition
Implementation Issues and Practical Examples of SVMs
Example of Detecting Voltage Dips Due to Faults
Rule-Based Expert Systems for Classification of Power System Events
Structure and Rules of Expert Systems
Application of Expert Systems to Event Classification
Summary and Conclusions
Event Statistics
Interruption Statistics
IEEE Standard 1366
Transmission System Indices
Major Events
Voltage Dips: Site Indices
Residual Voltage and Duration Data
Scatter Plot
Density and Distribution Functions
Two-Dimensional Distributions
SARFI Indices
Single-Index Methods
Year-to-Year Variations
Comparison Between Phase-Ground and Phase-Phase Measurements
Voltage Dips: Time Aggregation
Need for Time Aggregation
Time Between Events
Chains of Events for Four Different Sites
Impact on Site Indices
Voltage Dips: System Indices
Scatter Plots
Distribution Functions
Contour Charts
Seasonal Variations
Voltage-Dip Tables
Effect of Time Aggregation on Voltage-Dip Tables
SARFI Indices
Single-Index Methods
Summary and Conclusions
Voltage Dips
Time Aggregation
Stochastic Prediction Methods
Other Events
Events and Variations
Power Quality Variations
Power Quality Events
Itemization of Power Quality
Signal-Processing Needs
Variations and Events
Event Classification
IEC Standards on Power Quality
IEEE Standards on Power Quality